Hierarchical Bayesian Modeling of Decision-Making Tasks
Fit an array of decision-making tasks with computational models in
a hierarchical Bayesian framework. Can perform hierarchical Bayesian analysis of
various computational models with a single line of coding.
Sep 11, 2018 (0.6.0)
- Add new tasks (Balloon Analogue Risk Task, Choice under Risk and Ambiguity Task, Probabilistic Selection Task, Risky Decision Task (a.k.a. Happiness task), Wisconsin Card Sorting Task)
- Add a new model for the Iowa Gambling Task (igt_orl)
- Change priors (Half-Cauchy(0, 5) --> Half-Cauchy(0, 1) or Half-Normal(0, 0.2)
- printFit function now provides LOOIC weights and/or WAIC weights
March 26, 2018 (0.5.1)
- Add models for the Two Step task
- Add models without indecision point parameter (alpha) for the PRL task (prl_*_woa.stan)
- Model-based regressors for the PRL task are now available
- For the PRL task & prl_fictitious.stan & prl_fictitious_rp.stan --> change the range of alpha (indecision point) from [0, 1] to [-Inf, Inf]
Dec 25, 2017 (0.5.0)
- Support variational Bayesian methods (vb=TRUE)
- Allow posterior predictive checks, except for drift-diffusion models (inc_postpred=TRUE)
- Add the peer influence task (Chung et al., 2015, USE WITH CAUTION for now and PLEASE GIVE US FEEDBACK!)
- Add 'prl_fictitious_rp' model
- Made changes to be compatible with the newest Stan version (e.g., // instead of # for commenting).
- In 'prl_*' models, 'rewlos' is replaced by 'outcome' so that column names and labels would be consistent across tasks as much as possible.
- Email feature is disabled as R mail package does not allow users to send anonymous emails anymore.
- When outputs are saved as a file (*.RData), the file name now contains the name of the data file.
May 20, 2017 (0.4.0)
- Add a choice reaction time task and evidence accumulation models
- Drift diffusion model (both hierarchical and single-subject)
- Linear Ballistic Accumulator (LBA) model (both hierarchical and single-subject)
- Add PRL models that can fit multiple blocks
- Add single-subject versions for the delay discounting task (
- Standardize variable names across all models (e.g.,
outcome for all models)
- Separate versions for CRAN and GitHub. All models/features are identical but the GitHub version contains precompilled models.
Jan 22, 2017 (0.3.1)
- Remove dependence on the modeest package. Now use a built-in function to estimate the mode of a posterior distribution.
- Rewrite the "printFit" function.
Jan 20, 2017 (0.3.0)
- Made several changes following the guidelines for R packages providing interfaces to Stan.
- Stan models are precompiled and models will run immediately when called.
- The default number of chains is set to 4.
- The default value of
adapt_delta is set to 0.95 to reduce the potential for divergences.
- The “printFit” function uses LOOIC by default. Users can select WAIC or both (LOOIC & WAIC) if needed.
Dec 28, 2016 (0.2.3.3)
- Add help files
- Add a function for checking Rhat values (rhat).
- Change a link to its tutorial website
Dec 21, 2016 (0.2.3.2)
- Use wide normal distributions for unbounded parameters (gng_* models).
- Automatic removal of rows (trials) containing NAs.
Sep 29, 2016 (0.2.3.1)
- Add a function for plotting individual parameters (plotInd)
Sat July 16 2016 (0.2.3)
- Add a new task: the Ultimatum Game
- Add new models for the Probabilistic Reversal Learning and Risk Aversion tasks
- ‘bandit2arm’ -> change its name to ‘bandit2arm_delta’. Now all model names are in the same format (i.e., TASK_MODEL).
- Users can extract model-based regressors from gng_m* models
- Include the option of customizing control parameters (adapt_delta, max_treedepth, stepsize)
- ‘plotHDI’ function -> add ‘fontSize’ argument & change the color of histogram
Sat Apr 02 2016 (0.2.1)
- Bug fixes
- All models: Fix errors when indPars=“mode”
- ra_prospect model: Add description for column names of a data (*.txt) file
- Change standard deviations of ‘b’ and ‘pi’ priors in gng_* models
Fri Mar 25 2016 (0.2.0)